Overview

Dataset statistics

Number of variables17
Number of observations1 065
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory141.6 KiB
Average record size in memory136.1 B

Variable types

NUM15
CAT2

Warnings

Paris_max is highly correlated with Paris_min and 1 other fieldsHigh correlation
Paris_min is highly correlated with Paris_max and 1 other fieldsHigh correlation
Paris_avg is highly correlated with Paris_min and 1 other fieldsHigh correlation
reactions is highly correlated with retweetCount and 1 other fieldsHigh correlation
retweetCount is highly correlated with reactionsHigh correlation
likeCount is highly correlated with reactionsHigh correlation
reactionsAvg is highly correlated with retweetAvg and 1 other fieldsHigh correlation
retweetAvg is highly correlated with reactionsAvgHigh correlation
likeAvg is highly correlated with reactionsAvgHigh correlation
quoteAvg is highly skewed (γ1 = 21.88984396) Skewed
date has unique values Unique
quoteCount has 86 (8.1%) zeros Zeros
quoteAvg has 92 (8.6%) zeros Zeros
contest has 765 (71.8%) zeros Zeros

Reproduction

Analysis started2021-01-14 16:43:51.915944
Analysis finished2021-01-14 16:44:25.716474
Duration33.8 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

date
Categorical

UNIQUE

Distinct1065
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
2019-12-25
 
1
2018-03-17
 
1
2018-12-08
 
1
2019-05-15
 
1
2020-10-15
 
1
Other values (1060)
1060 
ValueCountFrequency (%) 
2019-12-2510.1%
 
2018-03-1710.1%
 
2018-12-0810.1%
 
2019-05-1510.1%
 
2020-10-1510.1%
 
2018-09-2010.1%
 
2020-07-2510.1%
 
2019-11-2310.1%
 
2019-12-0710.1%
 
2020-03-1110.1%
 
Other values (1055)105599.1%
 
2021-01-14T17:44:25.839651image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1065 ?
Unique (%)100.0%
2021-01-14T17:44:26.029207image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length10
Mean length10
Min length10

Paris_weather
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.3 KiB
3
594 
2
408 
1
 
59
0
 
4
ValueCountFrequency (%) 
359455.8%
 
240838.3%
 
1595.5%
 
040.4%
 
2021-01-14T17:44:26.205074image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-01-14T17:44:26.299542image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:26.409733image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Paris_min
Real number (ℝ)

HIGH CORRELATION

Distinct38
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.55868545
Minimum-5
Maximum32
Zeros10
Zeros (%)0.9%
Memory size8.3 KiB
2021-01-14T17:44:26.543247image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-5
5-th percentile2
Q17
median12
Q318
95-th percentile23
Maximum32
Range37
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.699131786
Coefficient of variation (CV)0.5334261946
Kurtosis-0.5646446869
Mean12.55868545
Median Absolute Deviation (MAD)5
Skewness0.1190360116
Sum13375
Variance44.87836669
MonotocityNot monotonic
2021-01-14T17:44:26.700406image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%) 
7736.9%
 
12615.7%
 
9595.5%
 
8575.4%
 
10545.1%
 
19535.0%
 
16524.9%
 
15504.7%
 
13494.6%
 
18484.5%
 
Other values (28)50947.8%
 
ValueCountFrequency (%) 
-510.1%
 
-420.2%
 
-340.4%
 
-210.1%
 
-190.8%
 
ValueCountFrequency (%) 
3210.1%
 
3110.1%
 
3020.2%
 
2920.2%
 
2830.3%
 

Paris_max
Real number (ℝ)

HIGH CORRELATION

Distinct42
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.30985915
Minimum-2
Maximum40
Zeros2
Zeros (%)0.2%
Memory size8.3 KiB
2021-01-14T17:44:26.859193image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-2
5-th percentile6
Q111
median17
Q323
95-th percentile30
Maximum40
Range42
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.810234422
Coefficient of variation (CV)0.4512015004
Kurtosis-0.6476254895
Mean17.30985915
Median Absolute Deviation (MAD)6
Skewness0.1752608674
Sum18435
Variance60.99976173
MonotocityNot monotonic
2021-01-14T17:44:27.012722image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%) 
11656.1%
 
10595.5%
 
25585.4%
 
23484.5%
 
22474.4%
 
15474.4%
 
8464.3%
 
12464.3%
 
20464.3%
 
24434.0%
 
Other values (32)56052.6%
 
ValueCountFrequency (%) 
-210.1%
 
-110.1%
 
020.2%
 
160.6%
 
260.6%
 
ValueCountFrequency (%) 
4010.1%
 
3830.3%
 
3740.4%
 
3640.4%
 
3540.4%
 

Paris_avg
Real number (ℝ)

HIGH CORRELATION

Distinct71
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.9342723
Minimum-3
Maximum36
Zeros3
Zeros (%)0.3%
Memory size8.3 KiB
2021-01-14T17:44:27.176540image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum-3
5-th percentile4
Q19.5
median14.5
Q320.5
95-th percentile26.5
Maximum36
Range39
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.169792199
Coefficient of variation (CV)0.4800898266
Kurtosis-0.6280821958
Mean14.9342723
Median Absolute Deviation (MAD)5.5
Skewness0.1407584137
Sum15905
Variance51.40592017
MonotocityNot monotonic
2021-01-14T17:44:27.347025image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
9.5413.8%
 
8.5343.2%
 
21302.8%
 
10.5292.7%
 
12292.7%
 
20292.7%
 
15282.6%
 
15.5272.5%
 
11272.5%
 
17.5262.4%
 
Other values (61)76571.8%
 
ValueCountFrequency (%) 
-320.2%
 
-1.530.3%
 
-120.2%
 
030.3%
 
0.550.5%
 
ValueCountFrequency (%) 
3610.1%
 
34.510.1%
 
3310.1%
 
32.550.5%
 
3230.3%
 

tweetCount
Real number (ℝ≥0)

Distinct60
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.9342723
Minimum1
Maximum137
Zeros0
Zeros (%)0.0%
Memory size8.3 KiB
2021-01-14T17:44:27.509417image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q16
median10
Q321
95-th percentile38
Maximum137
Range136
Interquartile range (IQR)15

Descriptive statistics

Standard deviation12.46368405
Coefficient of variation (CV)0.8345692245
Kurtosis9.769656778
Mean14.9342723
Median Absolute Deviation (MAD)5
Skewness2.092820484
Sum15905
Variance155.3434202
MonotocityNot monotonic
2021-01-14T17:44:27.682154image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
7868.1%
 
5736.9%
 
6726.8%
 
9706.6%
 
8706.6%
 
10585.4%
 
4535.0%
 
3353.3%
 
11343.2%
 
12343.2%
 
Other values (50)48045.1%
 
ValueCountFrequency (%) 
1181.7%
 
2232.2%
 
3353.3%
 
4535.0%
 
5736.9%
 
ValueCountFrequency (%) 
13710.1%
 
7410.1%
 
7110.1%
 
6610.1%
 
6310.1%
 

replyCount
Real number (ℝ≥0)

Distinct351
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean240.7352113
Minimum0
Maximum19166
Zeros1
Zeros (%)0.1%
Memory size8.3 KiB
2021-01-14T17:44:27.856267image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q121
median49
Q3140
95-th percentile806.6
Maximum19166
Range19166
Interquartile range (IQR)119

Descriptive statistics

Standard deviation968.2938212
Coefficient of variation (CV)4.02223595
Kurtosis180.1601348
Mean240.7352113
Median Absolute Deviation (MAD)35
Skewness11.67079742
Sum256383
Variance937592.9242
MonotocityNot monotonic
2021-01-14T17:44:28.028508image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
14252.3%
 
17191.8%
 
18181.7%
 
10181.7%
 
16171.6%
 
29171.6%
 
11161.5%
 
8161.5%
 
22161.5%
 
6161.5%
 
Other values (341)88783.3%
 
ValueCountFrequency (%) 
010.1%
 
150.5%
 
220.2%
 
360.6%
 
480.8%
 
ValueCountFrequency (%) 
1916610.1%
 
1288010.1%
 
948510.1%
 
788910.1%
 
674110.1%
 

retweetCount
Real number (ℝ≥0)

HIGH CORRELATION

Distinct458
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean915.1568075
Minimum0
Maximum71654
Zeros3
Zeros (%)0.3%
Memory size8.3 KiB
2021-01-14T17:44:28.205457image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q133
median93
Q3252
95-th percentile1750.6
Maximum71654
Range71654
Interquartile range (IQR)219

Descriptive statistics

Standard deviation5008.105393
Coefficient of variation (CV)5.472401398
Kurtosis98.75307096
Mean915.1568075
Median Absolute Deviation (MAD)73
Skewness9.354410085
Sum974642
Variance25081119.63
MonotocityNot monotonic
2021-01-14T17:44:28.374079image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
16141.3%
 
22131.2%
 
20131.2%
 
28121.1%
 
18121.1%
 
27121.1%
 
14111.0%
 
11111.0%
 
7111.0%
 
72100.9%
 
Other values (448)94688.8%
 
ValueCountFrequency (%) 
030.3%
 
140.4%
 
230.3%
 
340.4%
 
460.6%
 
ValueCountFrequency (%) 
7165410.1%
 
6041510.1%
 
5546610.1%
 
5230110.1%
 
4877210.1%
 

likeCount
Real number (ℝ≥0)

HIGH CORRELATION

Distinct794
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1259.823474
Minimum15
Maximum28362
Zeros0
Zeros (%)0.0%
Memory size8.3 KiB
2021-01-14T17:44:28.538501image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile120
Q1301
median596
Q31193
95-th percentile4388.6
Maximum28362
Range28347
Interquartile range (IQR)892

Descriptive statistics

Standard deviation2414.301019
Coefficient of variation (CV)1.916380405
Kurtosis54.08335345
Mean1259.823474
Median Absolute Deviation (MAD)362
Skewness6.409173438
Sum1341712
Variance5828849.412
MonotocityNot monotonic
2021-01-14T17:44:28.698585image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
16250.5%
 
20840.4%
 
17540.4%
 
43340.4%
 
27740.4%
 
14640.4%
 
35340.4%
 
74240.4%
 
23630.3%
 
45430.3%
 
Other values (784)102696.3%
 
ValueCountFrequency (%) 
1510.1%
 
1610.1%
 
2410.1%
 
2610.1%
 
2910.1%
 
ValueCountFrequency (%) 
2836210.1%
 
2836010.1%
 
2641610.1%
 
1983610.1%
 
1915110.1%
 

quoteCount
Real number (ℝ≥0)

ZEROS

Distinct117
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.93802817
Minimum0
Maximum5751
Zeros86
Zeros (%)8.1%
Memory size8.3 KiB
2021-01-14T17:44:28.859316image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median6
Q315
95-th percentile74.2
Maximum5751
Range5751
Interquartile range (IQR)13

Descriptive statistics

Standard deviation261.2853745
Coefficient of variation (CV)6.710287776
Kurtosis299.1708256
Mean38.93802817
Median Absolute Deviation (MAD)5
Skewness15.984958
Sum41469
Variance68270.04691
MonotocityNot monotonic
2021-01-14T17:44:29.023951image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
211010.3%
 
1928.6%
 
0868.1%
 
3847.9%
 
4746.9%
 
5575.4%
 
6575.4%
 
9393.7%
 
10353.3%
 
7333.1%
 
Other values (107)39837.4%
 
ValueCountFrequency (%) 
0868.1%
 
1928.6%
 
211010.3%
 
3847.9%
 
4746.9%
 
ValueCountFrequency (%) 
575110.1%
 
438510.1%
 
238810.1%
 
207610.1%
 
206310.1%
 

reactions
Real number (ℝ≥0)

HIGH CORRELATION

Distinct869
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2454.653521
Minimum16
Maximum106632
Zeros0
Zeros (%)0.0%
Memory size8.3 KiB
2021-01-14T17:44:29.197650image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile146.6
Q1373
median799
Q31679
95-th percentile7281.8
Maximum106632
Range106616
Interquartile range (IQR)1306

Descriptive statistics

Standard deviation8004.028325
Coefficient of variation (CV)3.260756867
Kurtosis86.4412054
Mean2454.653521
Median Absolute Deviation (MAD)506
Skewness8.598996704
Sum2614206
Variance64064469.43
MonotocityNot monotonic
2021-01-14T17:44:29.364698image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
46650.5%
 
21150.5%
 
42840.4%
 
19640.4%
 
88240.4%
 
43130.3%
 
53630.3%
 
44830.3%
 
25130.3%
 
32230.3%
 
Other values (859)102896.5%
 
ValueCountFrequency (%) 
1610.1%
 
1710.1%
 
2510.1%
 
3010.1%
 
3410.1%
 
ValueCountFrequency (%) 
10663210.1%
 
9678310.1%
 
9570110.1%
 
8033410.1%
 
7053910.1%
 

replyAvg
Real number (ℝ≥0)

Distinct297
Distinct (%)27.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.71492958
Minimum0
Maximum538
Zeros1
Zeros (%)0.1%
Memory size8.3 KiB
2021-01-14T17:44:29.519517image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.1
Q12.2
median4.2
Q39.6
95-th percentile57.88
Maximum538
Range538
Interquartile range (IQR)7.4

Descriptive statistics

Standard deviation47.98885123
Coefficient of variation (CV)3.053710868
Kurtosis63.86485253
Mean15.71492958
Median Absolute Deviation (MAD)2.5
Skewness7.384708025
Sum16736.4
Variance2302.929843
MonotocityNot monotonic
2021-01-14T17:44:29.694689image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
2323.0%
 
1.8262.4%
 
1242.3%
 
3242.3%
 
1.6242.3%
 
2.8212.0%
 
1.4201.9%
 
1.9201.9%
 
2.2191.8%
 
1.7191.8%
 
Other values (287)83678.5%
 
ValueCountFrequency (%) 
010.1%
 
0.410.1%
 
0.530.3%
 
0.630.3%
 
0.740.4%
 
ValueCountFrequency (%) 
53810.1%
 
523.210.1%
 
51810.1%
 
48710.1%
 
442.110.1%
 

retweetAvg
Real number (ℝ≥0)

HIGH CORRELATION

Distinct399
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.9741784
Minimum0
Maximum4856.4
Zeros4
Zeros (%)0.4%
Memory size8.3 KiB
2021-01-14T17:44:29.856476image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.5
Q13.6
median7.5
Q320.4
95-th percentile122.98
Maximum4856.4
Range4856.4
Interquartile range (IQR)16.8

Descriptive statistics

Standard deviation334.2173081
Coefficient of variation (CV)5.764933929
Kurtosis137.8956533
Mean57.9741784
Median Absolute Deviation (MAD)5.1
Skewness11.18405162
Sum61742.5
Variance111701.209
MonotocityNot monotonic
2021-01-14T17:44:30.024431image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.8171.6%
 
3.3171.6%
 
4171.6%
 
2.2151.4%
 
2151.4%
 
3.6141.3%
 
3.7141.3%
 
3141.3%
 
2.8131.2%
 
3.2131.2%
 
Other values (389)91686.0%
 
ValueCountFrequency (%) 
040.4%
 
0.120.2%
 
0.410.1%
 
0.640.4%
 
0.730.3%
 
ValueCountFrequency (%) 
4856.410.1%
 
4641.410.1%
 
4433.810.1%
 
4358.410.1%
 
2985.610.1%
 

likeAvg
Real number (ℝ≥0)

HIGH CORRELATION

Distinct754
Distinct (%)70.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98.50892019
Minimum2.7
Maximum2204
Zeros0
Zeros (%)0.0%
Memory size8.3 KiB
2021-01-14T17:44:30.195007image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum2.7
5-th percentile15.4
Q129.2
median52
Q3101.7
95-th percentile305.24
Maximum2204
Range2201.3
Interquartile range (IQR)72.5

Descriptive statistics

Standard deviation170.8700003
Coefficient of variation (CV)1.734563732
Kurtosis61.11687198
Mean98.50892019
Median Absolute Deviation (MAD)27.9
Skewness6.754999647
Sum104912
Variance29196.557
MonotocityNot monotonic
2021-01-14T17:44:30.829032image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
24.260.6%
 
28.750.5%
 
24.150.5%
 
3950.5%
 
4950.5%
 
34.750.5%
 
34.250.5%
 
16.640.4%
 
52.240.4%
 
28.840.4%
 
Other values (744)101795.5%
 
ValueCountFrequency (%) 
2.710.1%
 
6.610.1%
 
7.410.1%
 
7.510.1%
 
8.310.1%
 
ValueCountFrequency (%) 
220410.1%
 
2108.610.1%
 
1609.110.1%
 
1595.910.1%
 
1525.410.1%
 

quoteAvg
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct103
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.609014085
Minimum0
Maximum479.2
Zeros92
Zeros (%)8.6%
Memory size8.3 KiB
2021-01-14T17:44:30.981199image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.2
median0.5
Q31.1
95-th percentile6.46
Maximum479.2
Range479.2
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation17.05283953
Coefficient of variation (CV)6.536123982
Kurtosis582.1100901
Mean2.609014085
Median Absolute Deviation (MAD)0.3
Skewness21.88984396
Sum2778.6
Variance290.799336
MonotocityNot monotonic
2021-01-14T17:44:31.156937image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.212812.0%
 
0.310710.0%
 
0.4958.9%
 
0928.6%
 
0.5827.7%
 
0.1777.2%
 
0.6646.0%
 
0.8444.1%
 
0.7393.7%
 
1383.6%
 
Other values (93)29928.1%
 
ValueCountFrequency (%) 
0928.6%
 
0.1777.2%
 
0.212812.0%
 
0.310710.0%
 
0.4958.9%
 
ValueCountFrequency (%) 
479.210.1%
 
142.310.1%
 
118.510.1%
 
90.110.1%
 
86.510.1%
 

reactionsAvg
Real number (ℝ≥0)

HIGH CORRELATION

Distinct810
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean174.809108
Minimum3.3
Maximum7511
Zeros0
Zeros (%)0.0%
Memory size8.3 KiB
2021-01-14T17:44:31.318482image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile19.64
Q136.7
median67.8
Q3135.6
95-th percentile500.72
Maximum7511
Range7507.7
Interquartile range (IQR)98.9

Descriptive statistics

Standard deviation526.7717668
Coefficient of variation (CV)3.013411446
Kurtosis119.2081815
Mean174.809108
Median Absolute Deviation (MAD)38.5
Skewness10.05089503
Sum186171.7
Variance277488.4943
MonotocityNot monotonic
2021-01-14T17:44:31.490971image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
40.840.4%
 
51.640.4%
 
66.640.4%
 
56.540.4%
 
21.740.4%
 
2540.4%
 
27.140.4%
 
46.440.4%
 
8940.4%
 
24.740.4%
 
Other values (800)102596.2%
 
ValueCountFrequency (%) 
3.310.1%
 
9.210.1%
 
9.710.1%
 
9.910.1%
 
10.110.1%
 
ValueCountFrequency (%) 
751110.1%
 
7495.310.1%
 
6694.510.1%
 
6412.610.1%
 
444310.1%
 

contest
Real number (ℝ≥0)

ZEROS

Distinct11
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.523943662
Minimum0
Maximum12
Zeros765
Zeros (%)71.8%
Memory size8.3 KiB
2021-01-14T17:44:31.627713image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum12
Range12
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.138706989
Coefficient of variation (CV)2.173338607
Kurtosis20.25993441
Mean0.523943662
Median Absolute Deviation (MAD)0
Skewness3.673506457
Sum558
Variance1.296653606
MonotocityNot monotonic
2021-01-14T17:44:31.756520image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
076571.8%
 
117416.3%
 
2666.2%
 
3282.6%
 
5131.2%
 
4121.1%
 
630.3%
 
1210.1%
 
1010.1%
 
810.1%
 
ValueCountFrequency (%) 
076571.8%
 
117416.3%
 
2666.2%
 
3282.6%
 
4121.1%
 
ValueCountFrequency (%) 
1210.1%
 
1010.1%
 
810.1%
 
710.1%
 
630.3%
 

Interactions

2021-01-14T17:43:55.202306image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:55.345196image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:55.469595image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:55.601695image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:55.735363image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:55.871129image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.003935image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.139748image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.270121image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.397006image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.525350image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.652579image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.776484image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:56.903219image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:57.036676image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:57.172409image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:57.297307image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:57.411804image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:57.533437image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:57.668831image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:57.826096image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.090219image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.209320image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.331030image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.450217image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.569427image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.687709image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.802808image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:58.919885image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.043423image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.163210image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.294546image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.416997image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.546835image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.677697image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.812640image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:43:59.944490image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.071960image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.200700image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.328519image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.454307image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.580706image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.704470image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.831858image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:00.962292image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:01.091157image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:01.222722image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:01.346678image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:01.477665image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:01.608206image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:01.743403image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:01.876119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:02.001562image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:02.130684image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:02.417804image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:02.544822image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:02.671946image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:02.796090image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:02.922732image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.057429image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.185589image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.321124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.449443image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.585572image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.720302image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.858597image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:03.994615image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:04.133009image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:04.265635image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:04.395134image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:04.524687image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:04.654259image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:04.790383image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:04.949805image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:05.100205image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:05.232499image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:05.365143image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:05.492262image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:05.626656image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:05.758259image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:05.893048image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.027676image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.163803image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.293815image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.420741image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.547581image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.674652image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.800123image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:06.926472image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:07.066533image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:07.195200image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:07.320444image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:07.437633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:07.562425image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:07.901032image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.030211image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.165989image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.286957image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.410792image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.532085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.652238image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.773576image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:08.893643image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.028306image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.177506image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.300141image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.427737image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.547733image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.675734image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.804439image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:09.934436image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.063366image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.187886image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.314509image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.438154image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.571504image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.694333image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.815510image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:10.938220image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:11.067150image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:11.192183image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2021-01-14T17:44:11.436846image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2021-01-14T17:44:11.689263image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2021-01-14T17:44:14.840856image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2021-01-14T17:44:17.079283image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:17.204513image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
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2021-01-14T17:44:17.445728image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:17.569054image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:17.696530image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:17.823711image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:17.943295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.065799image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.185951image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.306581image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.423629image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.537061image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.653738image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.776904image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:18.899315image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.025869image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.154187image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.278782image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.405585image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.534214image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.660140image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.780765image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:19.905881image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.027687image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.157388image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.277311image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.394385image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.518047image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.643133image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.765334image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:20.897346image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.021996image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.163783image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.295187image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.429713image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.561256image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.688082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.817009image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:21.944453image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:22.076679image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:22.203719image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:22.332189image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:22.458696image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:22.589806image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.096595image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.225315image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.346339image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.474396image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.602295image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.733314image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.861799image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:23.986033image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:24.121531image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:24.247426image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:24.370263image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:24.493198image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:24.613493image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:24.736612image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:24.864371image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2021-01-14T17:44:31.908399image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-01-14T17:44:32.134387image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-01-14T17:44:32.352455image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-01-14T17:44:32.572839image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-01-14T17:44:25.136183image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-01-14T17:44:25.540362image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

dateParis_weatherParis_minParis_maxParis_avgtweetCountreplyCountretweetCountlikeCountquoteCountreactionsreplyAvgretweetAvglikeAvgquoteAvgreactionsAvgcontest
02018-01-012798.0822173806310042.821.6100.80.4125.50
12018-01-0225118.0323411756737211.13.717.70.122.50
22018-01-03291512.02241110953326107918.75.024.21.249.00
32018-01-042101412.031663449751213972.111.131.50.445.10
42018-01-0528119.5234512356847402.05.324.70.232.20
52018-01-062676.511178732254311.57.929.30.539.20
62018-01-072676.572319176759863.327.3109.60.7140.90
72018-01-083586.5292827511841415011.09.540.80.551.80
82018-01-092586.5213314457067531.66.927.10.335.90
92018-01-102787.5314412647156461.44.115.20.220.80

Last rows

dateParis_weatherParis_minParis_maxParis_avgtweetCountreplyCountretweetCountlikeCountquoteCountreactionsreplyAvgretweetAvglikeAvgquoteAvgreactionsAvgcontest
10552020-11-2136108.0744712002094242398363.9171.4299.134.6569.01
10562020-11-2237119.0885497107770172910.662.1134.68.8216.10
10572020-11-2328119.5827310952253216383734.1136.9281.627.0479.62
10582020-11-2427108.5158738312804717975.825.585.33.1119.81
10592020-11-2527119.010149495171161241614.949.5171.16.1241.62
10602020-11-26381210.0105843810834016195.843.8108.34.0161.90
10612020-11-2738119.51432210422142181368723.074.4153.012.9263.42
10622020-11-2837129.596540811436316797.245.3127.07.0186.60
10632020-11-2936108.081321232036564947791165.1290.0457.061.8973.90
10642020-11-303285.09100659139777223311.173.2155.28.6248.10